Nearcast: A Locality-Aware P2P Live Streaming Approach for Distance Education XUPING TU, HAI JIN, and XIAOFEI LIAO Huazhong University of Science and Technology and JIANNONG CAO Hong Kong Polytechnic University

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Nearcast A Locality-Aware P2P LiveStreaming
Approach for Distance EducationXUPING TU, HAI
JIN, and XIAOFEI LIAOHuazhong University of
Science and TechnologyandJIANNONG CAOHong Kong
Polytechnic University
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• Peer-to-peer (P2P) live video streaming has been
  widely used in distance education applications to
  deliver the captured video courses to a large
  number of online students.
• By allowing peers serving each other in the
  network, P2P technology overcomes many
  limitations in the traditional clientserver
  paradigm to achieve user and bandwidth
  scalabilities.
• However, existing systems do not perform well
  when the number of online students increases, and
  the system performance degrades seriously.
• One of the reasons is that the construction of
  the peer overlay in existing P2P systems has not
  considered the underlying physical network
  topology and can cause serious topology mismatch
  between the P2P overlay network and the physical
  network.
• The topology mismatch problem brings great link
  stress (unnecessary traffic) in the Internet
  infrastructure and greatly degrades the system
  performance.
• In this article, we address this problem and
  propose a locality-aware P2P overlay construction
  method, called Nearcast, which builds an
  efficient overlay multicast tree by letting each
  peer node choose physically closer nodes as its
  logical children.

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• In our previous work, we have developed a P2P
  media streaming system called Apple for
  delivering live video courses to remote online
  students Jin et al. 2004. However, Apple does
  not perform well when the number of the online
  students increases.
• The major reason is that the method for
  constructing the peer overlay in Apple does not
  consider the topology mismatch problem.

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• To address the topology mismatch issue, Nearcast
  builds an efficient overlay multicast tree by
  letting each peer node choose physically closer
  nodes as its logical children.
• The captured video course content is delivered
  from the root of the overlay tree.
• Each node on the tree can receive the media data
  from its upper-level nodes to play back while
  relaying it to the lower-level nodes.

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• Our proposed Nearcast also uses the tree-based
  method, but it differs from the above systems in
  that it takes into account the locality issue by
  assigning a well-designed, prebuilt coordinate to
  each peer through which it measures the distance
  and selects a close parent.
• Nearcast also considers the real-life network
  connectivity constraint issue, which is not
  addressed by any of the overlays already
  mentioned.

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PRELIMINARIES AND ASSUMPTIONS

• Each end host is aware of its own network
  position coordinate and connectivity constraint.
• The last hop(s) to an end host exhibits (exhibit)
  the lowest delay.
• The design of Nearcast has not considered a
  long-latency link, for example, a satellite link,
  as the last hop.
• For the latencies on the links between the nodes
  in the hierarchical physical network, the
  triangular inequality2 Guyton and Schwartz 1995
  holds.

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Tree Management

• To effectively construct and maintain the
  Nearcast tree, an end host should maintain a
  small amount of state information, including IP
  addresses and port numbers, layer numbers,
  connectivity constraints, and its network
  position coordinates, its parent and grandparent,
  the source host, and its children hosts.
• The layer number of an end host X, denoted by
  h(X), represents the order of the layer at which
  X is located in the Nearcast tree.
• The protocol for tree maintenance includes the
  operations for the host to join and depart from
  the overlay.

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Host Departure.

• We propose methods to handle a host departure
  that occurs gracefully or accidentally. A
  graceful departure occurs when a host X intends
  to leave the overlay, while an accident departure
  occurs when X fails.
• The failure of X can be detected by its children
  since the video data stream would be interrupted.
  For the graceful leaving procedure, X sends out
  Leave messages to both its parent and children.
• If a child receives the Leave message, it
  immediately sends a Rejoin message to its
  original grandparent. If a child detects that its
  parent has failed, it immediately sends out a
  Parent Leave message to its original
  grandparent.

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Results

• Control Overhead.
• From Figure 7 it can be seen that Nearcast
  carries much less control overhead compared with
  NICE and RTT. In NICE, group merging and division
  and periodically sending alive messages to each
  other for maintaining the group size lead to a
  large number of control messages and cause some
  stress on the routers.
• In RTT, there are many delay measurement messages
  injected into the overlay. In Nearcast, however,
  groups in each layer are organized by their
  locations, so there is little restriction on the
  group sizes.
• A peers availability is detected by the
  interruption of the media data stream
  transmission. Therefore, the number of the
  control messages is greatly reduced.

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Comparison of control overhead between Nearcast
and NICE.
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• Link Stress.
• From Figure 8(a), it can be found that, as the
  total number of nodes increases continuously,
  Nearcast has less average link stress than NICE,
  which slightly outperforms RTT. In NICE, the
  leader peer in each group knows only the
  distances between the peers within the group, but
  not the distances between the peers outside the
  group. Thus, while the media data stream expands
  outward, members in an upper-layer group may not
  always choose the nearest peer as their supplier.
  Therefore, the average link stress increases.
• In Nearcast, however, intentional reservation
  according to the network location value is used
  to organize the subtree of each layer.
• This helps the supplier selection, and improves
  the efficiency of the physical network.

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Fig. 8. Comparison of link stress between
Nearcast and NICE.
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• End-to-End Delay and ADP.
• Figure 9(a) shows the distribution of the average
  EED and the average ADP for different group
  sizes. In all cases, Nearcast is better than NICE
  in terms of EED.
• This also is due to the inaccuracy in the
  supplier selection in NICE. The RTT scheme uses
  the RTT directly as the metric to cluster the
  near peers, and thus can perform better tha the
  other two schemes in terms of EED. However, when
  the number of peers increases, the average link
  traffic increases so the EED becomes unstable and
  is usually different from the estimate of the
  first time.
• Consequently, the EED in RTT scheme becomes
  larger than that in Nearcast when the number of
  peers increases. As we can see in Figure 9(b),
  when there are a few peers in the multicas tree,
  the absolute latency in NICE and RTT is less than
  that in Nearcast.
• This is mainly because that Nearcast uses the
  peers capability of reservation to organize the
  multicast tree, so that the capability of the
  upper-layered peers is not fully utilized,
  leading to the growth in height of the multicast
  tree. However, as the system scale grows
  gradually, the reserved capability of the
  upper-layere peers is utilized, which improves
  the absolute latency.

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CONCLUSIONS

• In this article, we have presented Nearcast, a
  locality-aware P2P live video streaming approach
  to deliver video courses to a large number of
  remote students in distance education
  applications. Nearcast is a single-source overlay
  multicast approach that uses prebuilt network
  coordinates of the end hosts to organize the
  overlay multicast tree. It takes into
  consideration the topology mismatch problem and
  considers the network constraints, such as
  limited last-hop bandwidth and connectivity
  constraints in the tree construction and recovery
  procedures.We have evaluated the performance of
  Nearcast using both simulations and real
  deployment experiments. Compared to the existing
  approaches, Nearcast significantly improves the
  system performance with lower link stress and
  network latency.